Anova is one the most important topics in statistics. The word ANOVA is the abbreviation of analysis of variance. In general, Anova is the collection of statistical methods that are used for analyzing the means of groups as well as other associated procedures such as variance. The main purpose of Anova is to test the significant
differences between means of groups.
It is named as Anova because it is the analysis of means. In order to do that, the researcher actually tests the significant differences of variances because mean is the square root of variance. Variance is calculated as the sum of the squared deviations from the mean divided by sample size minus one.
If comparison between two means is performed, Anova produces same results as t-test does for independent samples.
If two different groups of observations are to be performed, then Anova produces same results as t-test does for dependent samples.
Classes of Anova Models
There are three classes of models of Anova described below:
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